1. Field of the Invention
The present invention relates to a moving picture compression system, and more particularly, to a block matching method for estimating a motion vector value by moving a target window.
The present application for a block matching method by moving a target window is based on Korean Application No. 97-13874 which is hereby incorporated by reference for all purposes.
2. Description of the Related Art
Generally, redundancy of a moving picture is removed in order to compress the moving picture. In most moving picture compression systems which are currently used, such as MPEG and H.261, a motion estimation method is used to remove the redundancy. The motion vector shows the position difference between a reference block and a matching block by dividing a current frame into various small reference blocks, comparing each reference block with various search area blocks of a previous frame in a given search area, calculating a difference measure, to which the search area blocks are different to the respective reference blocks, and finding the block having the smallest difference measure (hereinafter referred to as a matching block). Then, the above motion vector and a pixel difference between the reference block and the matching block are transferred.
A blocking matching algorithm (BMA) which is widely used for moving picture compression calculates which block of a next image frame is most related to a block of a predetermined size of the current image frame, on the basis of a mean square error. With the BMA, a variation value close to optimal can be found as the range of the target window becomes wider and more search points are found. However, this needs a huge amount of calculation, which makes coding difficult to perform in real time.
Generally, the background of a moving picture is the portion of a screen in which the most precise motion vector can be estimated. This is because the block is not so complicated, and the BMA is based on the fact that a motion vector value has little difference to its adjacent motion vector values. Namely, the target window does not change. Objects move in the same direction (a background screen usually does not move), and in particular, the image of a picture phone has one object of motion. Such a situation is easily assumed during panning. Better estimation can be performed considering such a correlation between adjacent motion variation values. However, the above BMA method has limitations in estimating the motion vector since the motion vector is obtained without considering the correlation with the adjacent motion vectors.